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unmodeled-tyler
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https://unmodeledtyler.substack.com

AI & ML interests

AI research engineer & solo operator of VANTA Research

Recent Activity

liked a model 3 days ago
NousResearch/Hermes-4-405B
reacted to alvdansen's post with 🚀 7 days ago
Releasing Flimmer today — a video LoRA training toolkit for WAN 2.1 and 2.2 that covers the full pipeline from raw footage to trained checkpoint. The standout feature is phased training: multi-stage runs where each phase has its own learning rate, epochs, and dataset, with the checkpoint carrying forward automatically. Built specifically with WAN 2.2's dual-expert MoE architecture in mind. Data prep tools are standalone and output standard formats — they work with any trainer, not just Flimmer. Early release, building in the open. LTX support coming next. http://github.com/alvdansen/flimmer-trainer
reacted to umarbutler's post with 🔥 7 days ago
This awesome visualization by @abdurrahmanbutler tracks how reliant the High Court of Australia has been on UK precedents over time. Back in the early 1900s, up to 70% of citations in High Court decisions were from the UK. Today, that number sits around 20%. This change seems to have happened gradually as Australia gained more and more independence from the UK, culminating in the Australia Acts of 1986, where we see a nice bump in the proportion of Australian cases cited. These insights would not be possible without our latest legal AI model, Kanon 2 Enricher, which we used to extract dates and citations from High Court decisions in https://huggingface.co/datasets/isaacus/open-australian-legal-corpus and categorize citations by jurisdiction. You can learn about Kanon 2 Enricher here: https://isaacus.com/blog/kanon-2-enricher.
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